Brandon W. Gordon

Development of advanced FDD and FTC techniques with application to an unmanned quadrotor helicopter testbed

Abstract As the first part, this paper presents an overview on the existing works on fault detection and diagnosis (FDD) and fault-tolerant control (FTC) for unmanned rotorcraft systems. Considered faults include actuator and sensor faults for single and multi-rotor systems. As the second part, several FDD and FTC techniques developed recently at the Networked Autonomous Vehicles Lab of Concordia University are detailed along with experimental application to a unique and newly developed quadrotor helicopter testbed.

Fault tolerant control of a quadrotor UAV using sliding mode control

In this paper, the sliding mode approach is used to control of a quadrotor unmanned aerial vehicle (UAV) in the presence of external disturbance and actuator fault. Fault detection unit can detect the actuator fault using a state estimator. Then it reconfigures the structure of controller such that some control performance is achieved. The proposed control structure has the advantage of disturbance rejection in the fault-free condition. Moreover it can recover some of control performances when a fault occurs. Different simulations have been carried out to show the performance and effectiveness of the proposed method.

Fault Tolerant Model Predictive Control of Quad-Rotor Helicopters with Actuator Fault Estimation

Abstract Model predictive control (MPC) at each time step minimizes a cost function subject to dynamical constraints to obtain a stabilizing control signal. Further, MPC is one of the few methodologies that can be used to design feedback control for nonlinear dynamical systems taking into consideration of actuator saturations. It can thus serve as a suitable fault tolerant control approach for quad-rotor helicopter governed by nonlinear dynamics. However, MPC needs a relatively accurate model of the post-failure system to calculate a stabilizing control signal. The problem becomes more critical where the system dynamics is described by a nonlinear model, because there exist few effective nonlinear parameter estimators with reasonable online computation time. To address this issue, for online actuator fault estimation, this paper investigates Moving Horizon Estimation (MHE) and Unscented Kalman Filter (UKF) as two methods for nonlinear parameter estimation. A framework is then formulated for integrating MHE/UKF based fault estimator with MPC to form an active fault tolerant control system for systems with nonlinear constrained dynamics. Performance and computation requirement of both algorithms are also investigated.

Passive and active nonlinear fault-tolerant control of a quadrotor unmanned aerial vehicle based on the sliding mode control technique

In this paper, an augmented sliding mode-based fault-tolerant control is designed theoretically, implemented practically and tested experimentally in a quadrotor unmanned aerial vehicle testbed under propeller damage and actuator fault conditions for tracking control. In view of the significant feature of robustness inherent to the sliding mode control technique, the developed sliding mode-based fault-tolerant control strategies have been designed and implemented in the two currently and widely used types of fault-tolerant control strategy, i.e. passive and active, with the intention to investigate and compare the advantages, disadvantages and application considerations and limitations of these two different fault-tolerant control strategies in the tracking control problem of a quadrotor unmanned aerial vehicle application. Therefore, these two types of controller have been carried out in both theory and practice with and without the presence of faults. Both theoretical and experimental analyses demonstrated the effectiveness of the two sliding mode-based fault-tolerant control strategies in the application to the quadrotor unmanned aerial vehicle under a small level of actuator faults or damage. Detailed comparisons are also provided in the paper to demonstrate the capabilities, advantages and disadvantages of the two types of fault-tolerant tracking controller under different flight conditions in the presence of actuator faults and propeller damage.

Hierarchical Decentralized Receding Horizon Control of Multiple Vehicles with Communication Failures

This work presents a new approach for designing decentralized receding horizon controllers (DRHC) for cooperative multiple vehicle systems with inter-vehicle communication delays arising from communication failures. Using DRHC each vehicle plans its own state trajectory over a finite prediction time horizon. The neighboring vehicles then exchange their predicted trajectories at each sample time to maintain cooperation objectives. Such communication failures lead to large, inter-vehicle communication delays of exchanged information. Large inter-vehicle communication delays can potentially lead to degraded cooperation performance and unsafe vehicle motion. To maintain desired cooperation performance during faulty conditions, the proposed fault-tolerant DRHC architecture estimates the tail part of the neighboring vehicle trajectory that is unavailable due to communication delays. Furthermore, to address the safety of the team against possible collisions during faulty situations, a fault-tolerant DRHC is developed, which provides safety using a safe protection zone called a tube around the trajectory of faulty neighboring vehicles. The radius of the tube increases with communication delay and maneuverability. A communication failure diagnosis algorithm is also developed. The required communication capability for the fault-diagnosis algorithm and fault-tolerant DRHC suggests a hierarchical fault-tolerant DRHC architecture. Simulations of formation flight of miniature hovercrafts are used to illustrate the effectiveness of the proposed fault-tolerant DRHC architecture.

Decentralized Receding Horizon Control for Cooperative Multiple Vehicles Subject to Communication Delay

N this paper, a new approach is proposed for the decentralized receding horizon control (DRHC) of multiple cooperative vehicles with the possibility of communication failures leading to large intervehicle communication delay. Such large communication delays can lead to poor performance and even instability. The neighboring vehicles exchange their predicted trajectories at each sampletimetomaintainthecooperationobjectives.Itisassumedthat the communication failure is partial in nature, which in turn leads to large communication delays of the exchanged trajectories. The proposedfault-tolerantDRHCisbasedontwoextensionsofexisting work for the case of large communication delays. The first contributionisthedevelopment ofanewDRHC approachthat estimates thetrajectoryoftheneighboringvehiclesforthetailoftheprediction horizon, which would otherwise not be available due to the communication delay. In this approach, the tail of the cost function is estimated by adding extra decision variables in the cost function. A relatively small amount of existing work has investigated the implementation issues associated with exchange of trajectory information, but so far no work has proposed a tail estimation process to compensate for large delays. For instance, in [1–3], no prediction or estimation for the trajectory of neighboring vehicles is performed, and it is assumed that the neighboring vehicles remain at the last delayed states broadcasted by them. Such assumptions may yield poor performance for large communication delays because the constant state vector is not a good estimation of a trajectory of states in general. Similar issues are also investigated in [4,5]. The second contribution of this paper is an extension of the tubebased model predictive control (MPC) approach [6,7] for the case of thelargecommunicationdelaysinordertoguaranteethesafetyofthe fleet against possible collisions during formation control problems. The concept of the tube MPC [or tube receding horizon control (RHC)] in existing work [6,7] is normally used to calculate a robust bound on the states due to system uncertainty, whereas in this paper, the approach is used to calculate bounds that arise from large communication delays of the exchanged neighbor trajectories. The proposed algorithms in this paper are presented in the context of fault-tolerant control, as the communication delay/break may occur due to any failure and malfunction in the communication devices. Some examples of communication failures for the team of cooperative vehicles can be found in [8–10]. In [8], the wireless communicationpacketloss/delayisconsidered;oncethepacketloss/ delay occurs, the previous available trajectory of the faulty unmanned aerial vehicle (UAV) is extrapolated to predict the future reference trajectory. Also, in [9], the communication failure in formation flight of multiple UAVs leads to a break in the communicated messages that forces the fleet to redefine the communication graph. This paper is organized as follows. Section II deals with a general formulation of the decentralized receding horizon controller, and the corresponding algorithm for a fault-free (delay-free) condition. In Section III, a faulty condition is first defined, and a reconfigurable fault-tolerant controller is developed. A safety guarantee method forthefaultyconditionisalsodevelopedbasedontheconceptoftube RHC. In Section IV, the proposed algorithms are tested through simulation of a leaderless formation controller for a fleet of unmanned vehicles.

Cooperative multi-vehicle search and coverage problem in uncertain environments

A decentralized approach is proposed to solve a cooperative multi-vehicle search and coverage problem in uncertain environments. Two different types of vehicle are used for search and coverage tasks. The search vehicles have a priori probability maps of targets in the environment and they update these maps based on the measurement of their sensors during the search mission. They use a limited look-ahead dynamic programming algorithm to find their own path individually while their objective is to maximize the amount of information gathered by the whole team. The task of service vehicles is to spread out over the environment to optimally cover the terrain. A locational optimization technique is used to assign Voronoi regions to vehicles and the stability of coverage system is guaranteed using LaSalles invariance principle. The service vehicles modify their configuration using the updated probability maps which are provided by the search vehicles. Simulations show that the proposed approach offers improved performance compared to conventional coverage methods.

Uncertain Nonlinear Receding Horizon Control Systems Subject to Non-Zero Computation Time

In this paper Receding Horizon Control (RHC) of an uncertain nonlinear system is considered where the computation time is non-negligible. In a well-known method, the solution process of the optimal control problem is started one sampling period in advance by using the prediction of the initial conditions, thus giving the controller a reasonable deadline to complete the optimization process. The current work suggests the use of the theory of neighboring extremal paths to improve the performance of the existing method by adding a correction phase to the previous method and therefore recovering the exact solution in the presence of prediction errors. An immediate result would be that the properties of the RHC techniques involving zero computation time would be valid for practical systems in the actual implementation, where a zero computation time is unachievable. The new approach is applied for the control of a mobile robot system which demonstrates significant performance improvements over the existing method.

Cooperative multi-vehicle search and coverage problem in an uncertain environment

A distributed approach is proposed in this paper to address a cooperative multi-vehicle search and coverage problem in an uncertain environment such as forest fires monitoring and detection. Two different types of vehicles are used for search and coverage tasks: search and service vehicles. The search vehicles have a priori probability maps of targets in the environment. These vehicles update the probability maps based on their sensors measurements during the search mission. The search vehicles use a limited look-ahead dynamic programming algorithm to find their own path individually while their objective is to maximize the amount of information gathered by the whole team. The task of the service vehicles is to optimally spread out over the environment to cover the interested area for a mission. A Voronoi-based coverage control strategy is proposed to modify the configuration of service vehicles in such a way that a prescribed coverage cost function is minimized using the updated probability maps which are provided by the search vehicles. The improved performance of the proposed approach compared to conventional coverage methods is demonstrated by numerical simulation and experimental results. Language: en

Decentralized Model Predictive Control for Cooperative Multiple Vehicles Subject to Communication Loss

The decentralized model predictive control (DMPC) of multiple cooperative vehicles with the possibility of communication loss/delay is investigated. The neighboring vehicles exchange their predicted trajectories at every sample time to maintain the cooperation objectives. In the event of a communication loss (packet dropout), the most recent available information, which is potentially delayed, is used. Then the communication loss problem changes to a cooperative problem when random large communication delays are present. Such large communication delays can lead to poor cooperation performance and unsafe behaviors such as collisions. A new DMPC approach is developed to improve the cooperation performance and achieve safety in the presence of the large communication delays. The proposed DMPC architecture estimates the tail of neighbors trajectory which is not available due to the large communication delays for improving the performance. The concept of the tube MPC is also employed to provide the safety of the fleet against collisions, in the presence of large intervehicle communication delays. In this approach, a tube shaped trajectory set is assumed around the trajectory of the neighboring vehicles whose trajectory is delayed/lost. The radius of tube is a function of the communication delay and vehicles maneuverability (in the absence of model uncertainty). The simulation of formation problem of multiple vehicles is employed to illustrate the effectiveness of the proposed approach.